Bulletin of Monetary Economics and Banking, Vol. 22, No. 1 (2019), pp. 47 - 68
CAPITAL REGULATION AND ISLAMIC BANKING
PERFORMANCE: PANEL EVIDENCE
Mansor H. Ibrahim1
1International Centre for Education in Islamic Finance, Kuala Lumpur, Malaysia.
Email: mansorhi@inceif.org
ABSTRACT
This paper empirically assesses the relation between bank performance and capital regulation for Islamic banks from 13 countries and evaluates whether the relation varies with bank size, capital, and liquidity. We find small Islamic banks to be less stable and less profitable; they also cut lending growth as capital regulation becomes more stringent. The stability and lending growth of big Islamic banks are, however, directly related to capital regulation. Further, capital regulation adversely affects the profitability of Islamic banks with low liquidity and high capital holdings. While capital regulation is needed, it should not be adopted in a blanket manner for all Islamic banks.
Keywords: Capital regulation; Islamic banks;
JEL Classification: C23; G21; G28.
Article history: |
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Received |
: January 17, 2019 |
Revised |
: March 10, 2019 |
Accepted |
: April 1, 2019 |
Available online : April 30, 2019
https://doi.org/10.21098/bemp.v22i1.1029
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I. INTRODUCTION
The rapid growth of Islamic banking in both size and complexity poses a key challenge in ensuring financial soundness in countries with both conventional and Islamic banks (IMF, 2017). While there are gaps and differences in Islamic banking regulatory frameworks across countries, Islamic banking is normally subject to the same banking regulations or regulatory environments as faced by conventional banks in their respective countries, particularly with respect to capital regulation and capital stringency requirements. Unfortunately, to date, there is a dearth of guidance in the literature on the effects of the stringency of capital requirements on Islamic bank performance. Moreover, existing findings for conventional banks may not be generalized to Islamic banks, due to their different business model. This begs the following questions: Is capital regulation of conventional banks applicable to Islamic banks? Is capital regulation effective in ensuring Islamic banking stability? Would capital regulation erode Islamic banking profitability or lending activity? And most importantly, does capital regulation fit Islamic banks with different
In light of these questions, the present paper assesses the relation between capital stringency regulation and Islamic banking performance. While we focus exclusively on capital stringency regulation, which aligns most closely to Basel capital standards, we contribute to the literature on the subject on various fronts. First, this paper provides a more comprehensive look at the issue for Islamic banks. While existing Islamic banking literature on the subject focuses mainly on only one aspect of performance, bank risk, we evaluate the implications of capital regulation on bank risk or stability, bank profitability, and lending behavior. Second, we address the question as to whether capital regulation fits Islamic banks with varying
Our results suggest that capital regulation does not affect all Islamic banks equally. Small Islamic banks seem to be more adversely affected; that is, they become less stable and less profitable and cut lending growth as capital regulation becomes more stringent. By contrast, the stability and lending growth of large Islamic banks are positively associated with capital regulation. We also find evidence indicating that the profitability of Islamic banks with low liquidity is adversely affected by capital regulation. Interestingly, capital regulation negatively affects the profitability of highly capitalized Islamic banks, while it has no implications for their stability and lending growth. These results hint at the importance of capital regulation for Islamic banks given that they have increased in size and complexity over the years. Still, capital regulation should not be adopted as a blanket rule
Capital Regulation and Islamic Banking Performance: Panel Evidence |
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applicable to all Islamic banks, especially in those countries where Islamic banks are small or in their infancy.
This paper unfolds as follows. Section II reviews the related literature. Section
IIIdetails the variables and empirical models. Section IV presents estimation results and, finally, Section V sets forth conclusions.
II. RELATED LITERATURE
Capital regulation, which normally equates to capital requirements, and its relation to bank performance has been a subject of intense discussion, especially since the Global Financial Crisis. While capital regulation is intended to curb excessive risk- taking and ensure bank stability, there have been concerns over its undesirable effects. Indeed, the literature highlights both positive and negative effects of capital regulation, see Triki et al. (2017), Deli and Hasan (2017), Bermpei et al. (2018) and references therein. On the positive side, by encouraging capital holdings in excess of minimum capital requirements, capital regulation reduces the moral hazard problem, enhances loss absorption capacity, and improves monitoring and control of risk by shareholders. As a result, banks become more stable and profitable and have greater ability to enhance credit growth. On the negative side, capital regulation may lead to reduced lending as a result of downward adjustments of
Existing empirical studies remain inconclusive as to the nature of the relation between capital regulation and bank performance. For instance, Agoraki et al. (2011) and Tan and Floros (2013) provide supporting evidence for a
Some studies explore the possibility that documented variations in the relation between capital regulation and bank performance are shaped by such factors as
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capital regulation. Interestingly, they also document variations in the effects of different aspects of capital regulation. Focusing on 42 African countries, Triki et al. (2017) show that the efficiency gains from more stringent capital requirements materialize only for large banks and low risk banks. Using aggregate data from 50 advanced and emerging market economies, Fratzscher et al. (2016) document the substitute role of institutional quality for capital regulation in that the decline in credit growth and bank stability during the Global Financial Crisis is countered by greater supervisory independence; this counteracting effect is strongest in countries with poor institutions. Finally, evaluating the banking sectors of 69 emerging and developing economies, Bermpei et al. (2018) identify various aspects of institutions that condition the effects of bank regulation on stability. These include control of corruption, political stability, creditor rights, and rule of law.
Within the nascent and
While some studies consider bank capital either as a focal variable or a control variable in explaining Islamic bank performance, studies that focus directly on the effects of capital regulation on Islamic banks are rather scarce. Among the few recent studies in the literature, Alam (2014), Zins and Weill (2017), and Ibrahim and Rizvi (2017) are notable. Employing a panel sample of 70 Islamic banks and 165 conventional banks from 11
The present study adds to this line of research. We follow the recent trend in the literature by focusing on
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III. VARIABLES AND MODELS
This section first explains the variables, then presents the empirical models used to address the research objectives, i.e., (i) to examine the impacts of capital regulation on Islamic banking stability, profitability, and lending growth, and (ii) to assess whether these impacts vary with bank size, capital, and liquidity.
A. Variables
The variables representing bank performance, which form the set of dependent variables, are bank stability, bank profitability, and bank lending growth. We use
The key explanatory variable is the capital regulation index (CR) compiled by Barth et al. (2006, 2013). This index is based on various questions related to capital requirements from World Bank surveys, including whether the capital asset ratio is in line with Basel guidelines; whether it varies with market risk and unrealized loan losses; whether losses in securities portfolios and in foreign exchange are deducted from book value before minimum capital adequacy is determined; whether sources of funds used as capital are verified by regulatory/supervisory authorities; whether initial or subsequent injections of capital can be made using assets other than cash and government securities; and whether initial disbursement of capital can be made with borrowed funds. The surveys were published in 1998, 2002, 2006 and 2011 (Fratzscher et al., 2016). We follow Bermpei et al. (2018) in assigning values from the surveys to create the yearly capital regulation index. That is, the index from the 1998 survey is assigned to the
We also include as explanatory variables several
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and Triki at el. (2017), we measure bank size using the natural log of total assets (LnTA). In addition, it is widely viewed that bank capital and liquidity can absorb shocks, making banks more stable as a result, although both capital and liquidity tend to be more costly and yield lower returns. We use the
Data on
B. Empirical Models
To assess the relation between capital regulation and Islamic bank performance, we begin with the following basic model:
(1)
PF is a measure of Islamic bank performance, namely, bank stability (LnZ), bank profitability (ROA), or bank lending growth (ΔLOAN). We include the lagged performance measure to allow for its persistence. CR is capital regulation. BS is a vector of
The key coefficient in (1) is β1, which measures the relation between bank performance and capital regulation. While capital regulation aims to ensure bank stability, there is concern that it may place undue constraints on banks or have undesirable effects on bank performance. Moreover, capital regulation may not fit all banks equally. Accordingly, to address whether the impacts of capital regulation vary with
(2)
Capital Regulation and Islamic Banking Performance: Panel Evidence |
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where bs is one of the
(3)
Thus, for concreteness, we compute and graph these marginal effects across bs values as suggested by Brambor et al. (2006).
There are small variations in model specification across the three bank performance equations, and hence their estimation strategies. In particular, we drop the lagged dependent variable in the lending growth equation, since it turns out to be insignificant, and estimate it using the
IV. ESTIMATION RESULTS
Our analysis focuses exclusively on Islamic banking and its relation to capital regulation. We gather
Table 1.
Variable Means by Country
This table reports the means of the variables by country.
|
CR |
TA |
EQA |
LIQA |
CIR |
ΔY |
INF |
|||
Bahrain |
88.21 |
1.90 |
15.17 |
5.39 |
3,271.07 |
20.88 |
18.15 |
58.69 |
5.14 |
2.14 |
Bangladesh |
33.06 |
1.13 |
24.73 |
4.57 |
1,297.93 |
6.85 |
19.34 |
45.90 |
5.80 |
6.76 |
Egypt |
54.14 |
0.69 |
3.07 |
2,657.71 |
5.44 |
19.02 |
71.54 |
4.14 |
8.52 |
|
Indonesia |
37.16 |
1.19 |
29.12 |
4.00 |
2,240.94 |
11.72 |
20.11 |
65.44 |
5.45 |
7.18 |
Jordan |
42.01 |
1.35 |
12.98 |
5.53 |
1,357.05 |
19.11 |
30.68 |
57.28 |
5.24 |
3.98 |
Kuwait |
48.29 |
1.55 |
9.42 |
5.11 |
11,215.69 |
14.88 |
24.02 |
60.39 |
5.01 |
1.93 |
Malaysia |
82.04 |
0.76 |
17.12 |
4.94 |
7,680.70 |
8.15 |
26.31 |
50.94 |
5.06 |
2.46 |
Pakistan |
48.79 |
1.72 |
28.46 |
7.23 |
1,531.11 |
9.50 |
21.76 |
55.26 |
4.28 |
10.23 |
Qatar |
70.08 |
3.47 |
18.94 |
4.60 |
6,550.75 |
16.34 |
23.90 |
28.95 |
11.55 |
4.21 |
Saudi Arabia |
38.44 |
2.65 |
16.65 |
5.10 |
18,970.56 |
15.94 |
23.35 |
50.37 |
5.28 |
3.22 |
Tunisia |
124.71 |
1.70 |
11.30 |
4.71 |
393.76 |
21.72 |
39.51 |
48.13 |
3.72 |
7.34 |
Turkey |
43.21 |
1.54 |
22.89 |
4.00 |
5,194.89 |
10.78 |
20.10 |
73.53 |
4.17 |
13.56 |
UAE |
109.37 |
2.32 |
21.4 |
5.41 |
8,805.11 |
18.10 |
19.95 |
43.76 |
4.54 |
4.70 |
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We include only Islamic banks that have data available from 2005 or earlier, such that they cover at least two regulatory surveys by the World Bank. Given that the latest survey is from 2011, we view it reasonable to end our sample at 2014. With these considerations, we arrive at the final panel sample of 45 Islamic banks.
Table 2.
Descriptive Statistics and Correlation Coefficients
This table reports the descriptive statistics of the variables, namely their means and standard deviations and their pairwise correlation coefficients.
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Descriptive Stat |
Correlation Coefficients |
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Mean |
S.D. |
ROA |
LOAN |
TA |
EQA |
LIQA |
CIR |
Y |
INF |
CR |
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62.359 |
122.65 |
1.00 |
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ROA |
1.571 |
2.788 |
0.01 |
1.00 |
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LOAN |
0.174 |
0.266 |
0.21 |
1.00 |
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TA |
5,757.20 |
9,759.98 |
0.12 |
0.11 |
1.00 |
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EQA |
13.705 |
9.316 |
0.03 |
0.42 |
1.00 |
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LIQA |
22.198 |
12.771 |
0.01 |
0.00 |
0.01 |
1.00 |
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CIR |
54.756 |
51.352 |
0.03 |
1.00 |
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Y |
5.269 |
3..300 |
0.31 |
0.15 |
0.12 |
0.13 |
1.00 |
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INF |
5.364 |
6.097 |
0.02 |
0.08 |
0.01 |
0.04 |
1.00 |
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CR |
4.844 |
1.884 |
0.19 |
0.16 |
0.04 |
0.01 |
1.00 |
Table 1 shows the means of the variables by country while Table 2 presents descriptive statistics and their pairwise correlation coefficients. Several observations arise from the tables. First, despite the rapid growth of the Islamic banking sector in these countries, there are marked variations in the performance of Islamic banks across the 13 countries. We find Islamic banks in Tunisia to be most stable and those in Bangladesh to be least stable, as indicated by the
The estimation results are presented in Tables 3 to 5 for, respectively, bank stability, profitability, and lending growth. To ease interpretation and inferences on our key themes, we present the marginal effects of bank regulation on bank performance together with the 90% confidence interval for the three cases in Figures 1 to 3. Below, we discuss each case.
Capital Regulation and Islamic Banking Performance: Panel Evidence |
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A. Capital Regulation and Bank Stability
Table 3 reports regression results for the bank stability equation, while Figure 1 shows the marginal effects of capital regulation on bank stability. We find that using the first lag of the dependent variable is not sufficient to render the error terms uncorrelated. Accordingly, we extend the lagged dependent variable up to lag 2. Both the Hansen test statistics and the
Table 3.
Estimation Results – Bank Stability
This table reports the regression results for bank stability equation. The numbers in parentheses are
ΔYt
INFt
CRt
(1) |
(2) |
(3) |
(4) |
0.7435*** |
0.6879*** |
0.7449*** |
0.7440*** |
(0.000) |
(0.000) |
(0.000) |
(0.000) |
(0.001) |
(0.001) |
(0.001) |
(0.000) |
0.2419** |
0.2409** |
0.2447*** |
|
(0.012) |
(0.475) |
(0.013) |
(0.010) |
(0.131) |
(0.132) |
(0.401) |
(0.136) |
0.0063 |
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(0.557) |
(0.630) |
(0.538) |
(0.708) |
(0.090) |
(0.017) |
(0.074) |
(0.084) |
(0.007) |
(0.007) |
(0.010) |
(0.008) |
0.0647** |
0.0640** |
0.0652** |
0.0628** |
(0.019) |
(0.014) |
(0.016) |
(0.019) |
0.0022 |
0.0047 |
0.0032 |
0.0018 |
(0.806) |
(0.679) |
(0.743) |
(0.836) |
(0.361) |
(0.033) |
(0.610) |
(0.981) |
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Table 3.
Estimation Results – Bank Stability (contd.)
This table reports the regression results for bank stability equation. The numbers in parentheses are
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(1) |
(2) |
(3) |
(4) |
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0.0838** |
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(0.045) |
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(0.920) |
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(0.485) |
Constant |
4.6603 |
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(0.303) |
(0.187) |
(0.301) |
(0.239) |
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# Observations |
413 |
413 |
413 |
413 |
# Banks |
45 |
45 |
45 |
45 |
P(Hansen) |
0.2307 |
0.3003 |
0.2133 |
0.2553 |
P(AR1) |
0.0001 |
0.0001 |
0.0001 |
0.0001 |
P(AR2) |
0.3077 |
0.2719 |
0.3365 |
0.2963 |
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Figure 1. Marginal Effects of Capital Regulation on Bank Stability
This figure plots the marginal effects of capital regulation on bank stability across
(a) Bank Size
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Figure 1. Marginal Effects of Capital Regulation on Bank Stability (contd.)
This figure plots the marginal effects of capital regulation on bank stability across
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70 |
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(c) Bank Liquidity
.3 |
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16 |
.2 |
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14 |
.1 |
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70 |
The results in column (1) of Table 3 indicate no significant effect of capital regulation on bank risk. However, when we include the capital regulation – bank size interaction, we find the coefficient of capital regulation and its interaction with bank size to be significant at the 5% level, with negative and positive signs, respectively. This means that capital regulation hurts small Islamic banks but helps large Islamic banks. Figure 1, panel (a), illustrates these marginal effects exhaustively across bank sizes. The graph clearly suggests that, for small Islamic banks, increasing capital regulation stringency makes them less stable. This negative effect of capital regulation, however, declines as banks become larger
58 |
Bulletin of Monetary Economics and Banking, Volume 22, Number 1, 2019 |
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and, indeed, it turns positive for the largest bank in the sample, with assets over $82 billion. This result is in line with Ibrahim and Rizvi (2017), which documents favorable effects of capital regulation for large banks. It is also in line with Triki et al. (2017), who find evidence suggesting efficiency gains from more stringent capital requirements for large banks.
When we interact capital regulation with bank capital or bank liquidity, neither capital regulation nor the interaction terms are significant. However, since the insignificance of the individual variables forming the interaction and of the interaction terms does not indicate the insignificance of the marginal effects at all levels of conditioned variables (i.e., capital and liquidity), we graph the corresponding marginal effects in panel (b) and panel (c) of Figure 1. Both suggest that the levels of bank capital and bank liquidity do not affect capital regulation – stability relation.
As for the control variables, larger banks tend to be more stable and, as hinted by the results from column 2 of Table 3, the stability effect of bank size is enhanced by capital regulation stringency. In other words, as Islamic banks become large, greater capital regulation is needed to ensure their stability. Results also indicate that more profitable banks are less stable. Bokpin (2016) argues that if banks have overriding concerns over maintaining profitability, they take more risk. In line with this argument, in the process of ensuring profitability, Islamic banks take more risk. This would increase the variance of ROA and consequently lower
B. Capital Regulation and Bank Profitability
Table 4 reports results for the bank profitability equation. Accompanying these results is Figure 2, which plots the marginal effects of bank regulation on profitability across bank size, capital and liquidity. In this equation, bank stability and lending growth enter insignificantly in all regressions, hence their exclusion. The Hansen test statistics and
Capital Regulation and Islamic Banking Performance: Panel Evidence |
59 |
|
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Table 4.
Estimation Results – Bank Profitability
This table reports the regression results for bank profitability equation. The numbers in parentheses are
*p < 0.1, ** p < 0.05, *** p < 0.01.
|
(1) |
(2) |
(3) |
(4) |
0.4416*** |
0.4425*** |
0.4435*** |
0.4370*** |
|
|
(0.000) |
(0.000) |
(0.000) |
(0.000) |
|
(0.005) |
(0.004) |
(0.006) |
(0.004) |
|
(0.007) |
(0.008) |
(0.350) |
(0.007) |
0.0036 |
0.0040 |
0.0028 |
||
|
(0.842) |
(0.827) |
(0.868) |
(0.583) |
0.0020 |
0.0023 |
0.0024 |
0.0019 |
|
|
(0.762) |
(0.727) |
(0.710) |
(0.764) |
ΔYt |
0.1739** |
0.1760** |
0.1741** |
0.1730** |
|
(0.026) |
(0.019) |
(0.018) |
(0.025) |
INFt |
0.0266 |
0.0246 |
0.0266 |
0.0271 |
|
(0.243) |
(0.244) |
(0.241) |
(0.223) |
CRt |
0.2239 |
|||
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(0.048) |
(0.194) |
(0.121) |
(0.153) |
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0.0603 |
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0.0034 |
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(0.439) |
Constant |
28.1430*** |
31.3945*** |
25.4947*** |
28.7389*** |
|
(0.005) |
(0.003) |
(0.006) |
(0.003) |
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# Observations |
539 |
539 |
539 |
539 |
# Banks |
45 |
45 |
45 |
45 |
P(Hansen) |
0.3640 |
0.4247 |
0.4568 |
0.3778 |
P(AR1) |
0.0651 |
0.0627 |
0.0513 |
0.0618 |
P(AR2) |
0.9955 |
0.9980 |
0.9346 |
0.9646 |
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60 |
Bulletin of Monetary Economics and Banking, Volume 22, Number 1, 2019 |
|
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Figure 2. Marginal Effects of Capital Regulation on Bank Profitability
This figure plots the marginal effects of capital regulation on bank profitability across
(a) Bank Size
.5 |
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16 |
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18 |
(b) Bank Capital
1 |
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16 |
.75 |
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14 |
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70 |
Capital Regulation and Islamic Banking Performance: Panel Evidence |
61 |
|
|
Figure 2. Marginal Effects of Capital Regulation on Bank Profitability (contd.)
This figure plots the marginal effects of capital regulation on bank profitability across
.05 |
|
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(c) Bank Liquidity |
|||
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16 |
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70 |
In column (1), the coefficient of capital regulation (CR) is negative and significant at the 5% significance level. This suggests a reduction of profitability of
0.11percentage point as the level of capital stringency increases by 1 point. When we interact capital regulation with the three
(column 3). As noted above, in models with an interaction term, assessing the significance of the variables forming the interaction term must be based on the marginal effects as given in equation (3), and not independently on the coefficients of CR and the interaction terms. The marginal effects, as plotted in Figure 2, demonstrate that basing interpretation on the two coefficients separately would be misleading. The plots all indicate the role of bank size, capital, and liquidity in influencing the relation between capital regulation and profitability. Again, we note that small Islamic banks tend to be adversely affected by capital regulation. Moreover,
Interestingly, we note that profitability of highly capitalized Islamic banks is adversely affected by capital regulation (Figure 2, panel (b)). Perhaps holding high
62 |
Bulletin of Monetary Economics and Banking, Volume 22, Number 1, 2019 |
|
|
levels of capital is suboptimal and capital stringency further imposes constraints on the banks; as a result, profitability drops. In other words, this result may reflect the costs of both capital and capital regulation.
As for the control variables, we find profitability to be negatively related to bank size and
C. Capital Regulation and Bank Loans
Table 5 presents the estimation results for the loan growth equation, while Figure 3 plots the marginal effects of capital regulation on loan growth across bank sizes and levels of bank capital and liquidity. In conformity with Ibrahim and Rizvi (2018), the loan growth of Islamic banks does not exhibit persistence. That is, the lagged dependent variable is not significantly different from 0. Accordingly, we drop the lagged dependent variable from the equation. In addition, we find profitability to be significant, while risk is not significant. This leads us to include
Table 5.
Estimation Results – Bank Loan Growth
This table reports the regression results for loan growth equation. The numbers in parentheses are
*p < 0.1, ** p < 0.05, *** p < 0.01.
|
(1) |
(2) |
(3) |
(4) |
|
(0.017) |
(0.004) |
(0.015) |
(0.017) |
0.0034 |
||||
|
(0.841) |
(0.656) |
(0.406) |
(0.857) |
0.0043*** |
0.0041*** |
0.0041*** |
0.0047 |
|
|
(0.001) |
(0.001) |
(0.002) |
(0.130) |
0.0004 |
0.0004 |
0.0004 |
0.0004 |
|
|
(0.302) |
(0.297) |
(0.321) |
(0.300) |
0.0193*** |
0.0200*** |
0.0191*** |
0.0193*** |
|
|
(0.000) |
(0.000) |
(0.000) |
(0.000) |
Yt |
0.0072* |
0.0079** |
0.0069* |
0.0071* |
|
(0.078) |
(0.045) |
(0.098) |
(0.075) |
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Table 5.
Estimation Results – Bank Loan Growth (contd.)
This table reports the regression results for loan growth equation. The numbers in parentheses are
*p < 0.1, ** p < 0.05, *** p < 0.01.
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(2) |
(3) |
(4) |
INFt |
0.0027 |
0.0030 |
0.0029 |
0.0027 |
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(0.193) |
(0.173) |
(0.175) |
(0.197) |
CRt |
0.0012 |
0.0119 |
0.0029 |
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(0.848) |
(0.017) |
(0.259) |
(0.823) |
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0.0130** |
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(0.865) |
Constant |
0.4077** |
1.3109*** |
0.3587* |
0.4020* |
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(0.042) |
(0.005) |
(0.062) |
(0.057) |
# Observations |
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539 |
539 |
539 |
# Banks |
45 |
45 |
45 |
45 |
0.1166 |
0.1296 |
0.1196 |
0.1166 |
Figure 3. Marginal Effects of Capital Regulations on Lending Growth
This figure plots the marginal effects of capital regulation on loan growth across
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Figure 3. Marginal Effects of Capital Regulations on Lending Growth (contd.)
This figure plots the marginal effects of capital regulation on loan growth across
.15 |
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Again, bank size emerges as a significant factor shaping the relation between capital regulation and loan growth. Only in column (2), where we interact capital regulation with size, do we find both capital regulation and the interaction term to be significant. These results suggest that, for small Islamic banks, capital regulation stringency curtails loan growth. This negative effect of capital regulation on loan growth, however, is reversed when Islamic banks become larger. The marginal effects plotted in Figure 3, panel (a), reaffirm this interpretation. As for capital and liquidity, we do not find evidence suggesting that they condition the capital
Capital Regulation and Islamic Banking Performance: Panel Evidence |
65 |
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regulation – loan growth relation (see Figure 3). This finding is in line with the evidence provided in Deli and Hasan (2017) for a worldwide sample of banks. Although these authors note the significant role of bank capital in shaping the relation between capital requirements and credit growth, there is no permanent effect of capital regulation on loan growth.
As for the other control variables, we find a reduction in loan growth as bank size increases. Viewed together with the positive coefficient of the capital regulation – size interaction, i.e., column (2), the increase in loan growth by large banks materializes under stringent capital regulation requirements. This reaffirms our conclusion as to capital regulation and bank stability that, as Islamic banks become larger, more capital regulation is needed. We also find evidence that more liquid and more profitable banks tend to lend more. Finally, in line with many studies, we find lending growth of Islamic banks to move in tandem with business cycles (Ibrahim, 2016).
V. CONCLUSION
The Islamic banking sector has expanded rapidly over the years in many countries, especially in Malaysia and the Middle East. Being financial intermediaries, Islamic banks normally face the same regulatory environments as those initially designed for conventional banks, such as the Basel capital requirements and regulations. Given institutional differences between Islamic and conventional banks, the results obtained for conventional banks may not be applicable to Islamic banks. Thus, we assess the relation between capital regulation and Islamic bank risk, profitability, and loan growth and evaluate whether their relation varies with bank size, capital, and liquidity. Our results indicate heterogeneities in their relations, which are mainly conditioned by bank size.
More specifically, small banks are less stable, less profitable, and cut loan growth in the face of more stringent capital regulations. These negative effects, however, are subdued or even reversed when banks become larger. We also uncover evidence that the benefits of having large Islamic banks, in the form of improved stability and higher loan growth, manifest only when stringent capital regulation is in place. Apart from these findings, we also document evidence that the profitability of Islamic banks with low liquidity is adversely affected by capital regulation. Interestingly, the profitability of highly capitalized Islamic banks is also negatively affected by capital regulation. This may reflect the costly nature of both capital and capital regulation.
The policy implications of our results are clear. Capital regulation is important for Islamic banks, especially in countries where Islamic banks have grown in size and complexity. However, given the observed heterogeneities in the relation between capital regulation and bank performance, capital regulation should not be adopted blindly as a
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